Can sustainable investments outperform traditional benchmarks? Evidence from global stock markets

To contribute to overcoming global sustainability challenges, investors have been increasingly interested in making sustainable investments and incorporating environmental, social and governance (ESG) criteria into their portfolio selection decisions and managerial activities. However, these investors and other agents interested in sustainable investment need updated and robust information to support their decision making. We analyzed the performance of several Dow Jones Sustainability Indices (DJSIs) and compared them with their respective market benchmarks from 2013 to 2018. The indices comprise the following regions and countries: the world, the Asia‐Pacific, Europe, emerging markets and the US. The analysis was conducted based on both classic and modern portfolio metrics. The results suggest that sustainable investment performance is still heterogeneous worldwide, but there is a promising opportunity for investors to obtain superior risk‐adjusted returns in certain regions while incorporating sustainable investment practices. The findings are of utmost importance to financial market practitioners, business managers, academics and other stakeholders interested in promoting investments, corporate practices and scientific knowledge to achieve the Sustainable Development Goals (SDGs).     

The Impact of Distance (External) and Organizational Factors (Internal) on the Knowledge Chain of Multinational Corporations: South Africa as a Host Country

The geographic dispersion of multinational corporations (MNCs) implies that while it gives them access to new and different knowledge from diverse localities, it also adds to the costs and complexities of managing that knowledge and its effective dispersal across geographies. The purpose of this article is to examine how knowledge is transferred within MNCs and provide a framework for this process, particularly focusing on the role that distance (external) and organizational (internal) factors plays therein. A qualitative study is utilized, focusing on two technology companies from different cultural home countries and the technology transfer process with their South African subsidiaries. We find that the standardization of knowledge impacts the creation and diffusion of knowledge; expatriates impact on the creation, diffusion, and adoption; and, finally, relevance and localization impact on the adoption and utilization of knowledge. We present a conceptual framework around trust and rationalization as regards transferring knowledge within MNCs and find some evidence of the impact of distance, particularly cultural, on the methods employed in this transfer. The article illustrates the practical ways in which MNCs organize their internal resources and overcome various dimensions of distance in ensuring knowledge transfers. By choosing companies from such divergent home countries (one industrialized and one newly industrialized, with very different cultural settings) and examining their knowledge transfers with their South African subsidiaries, we are able to unpack various dimensions of distance and how organizational mechanisms affect this process. © 2017 Wiley Periodicals, Inc.     

Improving time series forecasting: An approach combining bootstrap aggregation,clusters and exponential smoothing

Some recent papers have demonstrated that combining bagging (bootstrap aggregating) with exponential smoothing methods can produce highly accurate forecasts and improve the forecast accuracy relative to traditional methods. We therefore propose a new approach that combines the bagging, exponential smoothing and clustering methods. The existing methods use bagging to generate and aggregate groups of forecasts in order to reduce the variance. However, none of them consider the effect of covariance among the group of forecasts, even though it could have a dramatic impact on the variance of the group, and therefore on the forecast accuracy. The proposed approach, referred to here as Bagged.Cluster.ETS, aims to reduce the covariance effect by using partitioning around medoids (PAM) to produce clusters of similar forecasts, then selecting several forecasts from each cluster to create a group with a reduced variance. This approach was tested on various different time series sets from the M3 and CIF 2016 competitions. The empirical results have shown a substantial reduction in the forecast error, considering sMAPE and MASE.     

Crypto-assets portfolio optimization under the omega measure

Abstract

Crypto-currencies, or crypto-assets, represent a new class of investment assets. The traditional portfolio analysis approach of Markowitz is not appropriate for use with portfolios containing crypto-assets, as the model requires that the investor have a quadratic utility function or that the returns be normally distributed, which isn’t the case for crypto-assets. We develop a portfolio optimization model based on the Omega measure which is more comprehensive than the Markowitz model, and apply this to four crypto-asset investment portfolios by means of a numerical application. The results indicate that these portfolios should favor traditional market assets over crypto-assets. In the case of portfolios formed only by crypto-assets, there is no clear preference in favor of any crypto-asset in particular.     

Cross‐country evidence on the determinants of inclusive growth episodes

Widening income disparities and slow productivity growth in most advanced and several emerging‐market economies have rekindled interest in the empirical analysis of the determinants of inclusive growth, defined in this paper as episodes of increases in GDP per capita without a concomitant deterioration in the distribution of household disposable income. The empirical analysis is based on a chronology of inclusive growth episodes between 1980 and 2013 for a sample of 78 countries. Logit and multinomial probit estimations show that human capital accumulation, the redistributive potential of tax‐benefit systems, increases in multifactor productivity and labor force participation, as well as trade openness and a range of institutional factors, including political system durability and electoral regimes, are important determinants of the probability of occurrence of inclusive growth. This empirical evidence contributes to the policy debate about how countries can deal with efficiency–equity tradeoffs.     

Multiples’ Valuation: The Selection of Cross-Border Comparable Firms

We studied whether mean industry multiples are similar in Brazil and in the United States. Using multilevel models (hierarchical linear model and additive crossed random-effects model), we concluded that there exists significant variability within firms from the same industry and significant variability between countries (Brazil and United States). The same tests were applied to firms grouped in clusters by similarity of economic fundamentals and we concluded that part of the variability shifts from (a) the variability within firms from the same industry and the variability between countries to (b) the variability between clusters, which is desirable in multiples’ valuation.     

Capital requirements,risk-taking and welfare in a growing economy

Journal of Regulatory Economics - The effects of capital requirements on risk-taking and welfare are studied in an overlapping generations model of endogenous growth with banking, limited...